The classification stage consisting of FC layers and a Softmax operator gives the probability of input pattern belonging to a specific class based on the feature maps extracted at the FE stage. FC layer connects every single neuron in the previous layer to every neuron in the current layer. In [1]} and [2]}, the authors proposed that the FC layer can be disregarded by using a global average pooling layer. Softmax is commonly used for classification tasks [3]}, [4]} however, many works have also utilized SVM [5]}, [6]} for this purpose.
